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CMAQ and REMSAD- Model Performance and Ongoing Improvements. Brian Timin, Carey Jang, Pat Dolwick, Norm Possiel, Tom Braverman USEPA/OAQPS December 3, 2002. Introduction. USEPA has performed an annual simulation of CMAQ and REMSAD for a 1996 base year
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CMAQ and REMSAD- Model Performance and Ongoing Improvements Brian Timin, Carey Jang, Pat Dolwick, Norm Possiel, Tom Braverman USEPA/OAQPS December 3, 2002
Introduction • USEPA has performed an annual simulation of CMAQ and REMSAD for a 1996 base year • An operational evaluation has been completed for both models • Performance evaluations have uncovered some weaknesses in the model formulation and inventories • OAQPS has identified a list of CMAQ model improvement priorities
1996 National CMAQ and REMSAD- Model Setup • CMAQ- May 2001 release w/MEBI solver • REMSAD- Version 7.01 • Model Setup: • Domain: • CMAQ and REMSAD: 36km, 12 layers, ~38 m surface layer • Emissions: • CMAQ and REMSAD: 1996 NEI w/adjustments, processed via SMOKE • Meteorology: 1996 MM5 • Chemistry: • CMAQ: CB-IV chemical mechanism w/ fast solver (MEBI) • REMSAD: micro-CB-IV chemical mechanism
Nationwide Modeling Domains CMAQ Modeling Domain REMSAD Modeling Domain CMAQ National domain is a Lambert conformal projection from 100°W, 40°N REMSAD uses a lat-long projection
Notes on Emission Inventory • Base Year 1996 NEI w/adjustments • Removal of wildfires, wind blown dust, and residential on-site incineration • PM Transport Factor • 75% reduction in fugitive dust sources • Adjusted CA NOx and VOC (non-EGU) • Revised Temporal Data • Prescribed burning • Animal husbandry • Used results from ORD inverse modeling (monthly reductions of 20-60%) • Annual NH3 inventory reduced by ~30% • Biogenic Emissions • BEIS 3.09
CMAQ and REMSAD Model Performance • Completed statistical comparison against observations for 12 layer REMSAD and CMAQ • Data sources: IMPROVE network; CASTNET dry dep. Network; NADP wet deposition network; CASTNET visibility network • All comparisons paired in time/space • Statistics and scatterplots for seasonal and annual averages • Calculated performance statistics by year and season for each monitoring site • Thousands of individual numbers; only presenting gross summary • Limited data base (in 1996) makes conclusive statements re: model performance difficult
IMPROVE Annual Average Performance StatisticsAnnual mean predicted/annual mean observed REMSAD CMAQ
July Average Organic Aerosols AE2 Aerosol
Winter Average NitrateCMAQ 1996 vs. Observed 2001-2002 (IMPROVE and Urban Speciation) Qualitative comparison of spatial patterns with more recent urban speciation data
Model Performance- Summary of Individual Species • CMAQ tends to predict higher concentrations than REMSAD; especially in the West • REMSAD slightly underpredicts sulfate in the East; CMAQ slightly overpredicts sulfate • Nitrate is overpredicted in the East • Total nitrate (particulate + nitric acid) is overpredicted in all seasons • Indicates an overestimation of nitric acid • REMSAD underpredicts organic carbon; CMAQ is relatively unbiased • Large uncertainty in the primary organic inventory (no wildfires), the organic measurements, and the secondary organic chemistry • CMAQ is predicting much more biogenic SOA; but it is using an aerosol yield approach (AE2) • Much of the biogenic SOA in REMSAD is being partitioned into the gas phase
Model Performance- Individual Species • Elemental carbon is generally unbiased • Large uncertainty in measurement of elemental carbon (EC/OC split) • IMPROVE sites have very low EC concentrations • Soil/other concentrations are overpredicted • Inventory issues • Fugitive dust, unspeciated emissions from construction, paved roads, etc. in urban areas • NADP wet concentration comparisons • Sulfate • CMAQ overpredicts in the East; REMSAD underpredicts • Nitrate • Both models overpredict in the East; REMSAD underpredicts in the West • Ammonium • REMSAD underpredicts; CMAQ slightly overpredicts in the East
Next Steps • Additional evaluation techniques can be applied • Further comparisons to more recent urban speciation data • Closer look at individual sites, days, seasons, regions • Time series plots • 20% best/worst days for visibility • Plan to model 2001 base year • Significantly more ambient data available • Continue to look at PM monitoring issues and how they affect model performance evaluation • Uncertainty in nitrate observed data • EC/OC split • Monitoring network protocol differences
OAQPS CMAQ Model Improvement Priorities (non-inventory) • Winter nitrate overprediction (general nitric acid overprediction) • Chemistry • Dry deposition • SOA overpredictions (biogenic) with 2002 release • Emission factors • Aerosol yields • Gas/particle partitioning • Horizontal diffusion • Relatively low explicit diffusion • Run times • Decreased run time will allow more refined modeling of longer time periods
Model Improvement Priorities(modeling inventory) • Ammonia inventory • Currently using adjusted 1996 inventory based on ORD monthly inverse modeling estimates • Need long term methodological improvements • Primary organic carbon • Need improved fire emissions • May be missing some organic sources • Primary semi-volatiles? • Primary unspeciated PM2.5 (PM-Other) • Modeled concentrations are grossly overestimated • Unspeciated fraction in certain speciation profiles is very high • Solid waste combustion (89% unspeciated) • Coal combustion (85% unspeciated) • Wood waste combustion (65% unspeciated)
Primary PM2.5 Emissions CMAQ- Partial Solution • The primary PM emissions in the 2001 CMAQ release were emitted in the wrong module • Emitted in the AERO module • Should be emitted in the VDIFF module • Problem corrected in the 2002 release • Primary PM2.5 concentrations reduced by 5-35%
July Average “PM-Other” Concentrations PM2.5-Other 2001 Release Ratio of 2002/2001 Release
Winter Nitrate- CMAQ vs. REMSAD • Much of the difference in winter nitrate predictions between CMAQ and REMSAD can be traced to different implementations of the dry deposition routines • Nitrate concentrations were found to be sensitive to dry deposition of NH3, HNO3, and NO2 • Improvements and adjustments are needed in both CMAQ and REMSAD, particularly in the areas of: • Treatment of snowcover and freezing temperatures • Specification of land use and surface roughness • Treatment of soluble species when canopies are wet • January nitrate concentrations agreed to within ~25% after the dry deposition routines were made more similar to each other through a series of sensitivity runs (with REMSAD)
January Nitrate Comparison After Dry Deposition Sensitivities
Dry Deposition- CMAQ • CMAQ contains 2 dry deposition routines; RADMDRY and M3DRY • M3DRY is a new routine • Many improvements over the old Wesely routine (RADMDRY) • MM5-PX (Pleim/Xiu land surface model) output is needed to take advantage of many of the improvements in M3DRY • Most significant change is enhanced deposition velocities for soluble species when canopy is wet • M3DRY does not currently have a “temperature function” or a specific treatment for snow or frozen ground • ORD is working on improvements to M3DRY • Adding freezing temperature and snowcovertreatment • M3DRY may increase dry deposition of soluble species (e.g NH3)
Additional Issues- CMAQ 2002 Release • CMAQ 2002 release contains new AE3 aerosol mechanism • Includes ISORROPIA nitrate partitioning and SOA gas/particle partioning • Ran sensitivity test of 2002 release with AE3 for January and July 1996 • Particulate nitrate increases due to heterogeneous chemistry • Gas phase N2O5 rate constant lowered • Added a heterogeneous N2O5 reaction to aerosol mechanism • N2O5---> HNO3 (particulate nitrate) • Biogenic SOA increases by a factor of 3 to 4 • AE3 biogenic SOA (July) is too high in parts of the country (especially the West) • Aerosol yields increased by a factor of 4 (in new release) • SOA partitioning is dominated by particle phase
AE2 vs AE3January Average Particulate Nitrate CMAQ 2001- AE2 CMAQ 2002- AE3 AE3 includes both effect of ISORROPIA and heterogeneous chemistry
AE2 vs AE3July Average Biogenic SOA CMAQ 2001- AE2 CMAQ 2002- AE3
SOA Gas/Particle PartitioningJuly Average % Biogenic SOA in Particle Phase
Horizontal Diffusion • Kh in CMAQ may be too low, especially at 36km resolution • CMAQ Kh is indirectly proportional to grid cell size • REMSAD, UAM-V, and CAMx Kh is directly proportional to grid cell size • At 36km resolution the Kh in CAMx is ~17,000 m2/sec and the Kh in CMAQ is ~25 m2/sec (both using PPM advection) • Which methodology is more scientifically correct?
Summary of OAQPS CMAQ Model Improvement Priorities (non-inventory) • Winter nitrate overprediction (general nitric acid overprediction) • Gas phase chemistry (daytime and nighttime) • Daytime NO2 + OH rate constant • SAPRC • CB-IV 2002 • Nighttime • N2O5 gas phase rate constant and heterogeneous reaction • Dry deposition (M3DRY routine) • Snowcover and freezing temperatures • Wet canopy • AE3 SOA overpredictions (biogenic) • Terpene emission factors • Aerosol yields • Gas/particle partitioning
Summary of OAQPS CMAQ Model Improvement Priorities (non-inventory) • Horizontal diffusion • Is current methodology OK? • Does CMAQ need more explicit diffusion when using “accurate” advection schemes (PPM and Bott)? • Run times • Can CMAQ be made to run faster? • 2001 release is 3 times slower than REMSAD • 2002 release (with CB-IV) is almost 4 times slower than REMSAD • SAPRC will slow it down even more • OAQPS is working with ORD to address all of the above issues